Combining GPT and Colab as learning tools for students to explore the numerical solutions of difference equations
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Department of Mathematics Statistics and Computers, Ubon Ratchathani University, Ubon Ratchathani, THAILAND
Department of Mathematics, Dongguk University, Seoul, SOUTH KOREA
Online publication date: 2023-11-16
Publication date: 2024-01-01
EURASIA J. Math., Sci Tech. Ed 2024;20(1):em2377
One of the most important things you can do to improve your mathematical application is to learn how to find numerical solutions. However, it was discovered that classrooms teaching methods that use numerical solutions are largely unable to provide students with the successful experience they should have in finding numerical solutions. Since conceptual and procedural knowledge, as well as the ability to perform computational mathematics, must be understood, simultaneously mastering all three can be difficult for most students. This study investigates combining GPT and Colab as learning tools for students to explore numerical solutions in the context of difference equations. The developed learning process works in tandem with the power of GPT and Colab to provide students with a successful experience in finding numerical solutions to difference equations. The survey results show that students have a high level of self-efficacy in finding numerical solutions to difference equations. This reflects today’s power of innovation, which can be applied in classroom to improve student skills so that they can use the tools to solve problems.
Alkhan, K., & Shaimova, Z. (2020). Teaching high school students to solve differential equations using Python at math class. Bulletin Series of Physics & Mathematical Sciences, 1(69), 38-43.
Alneyadi, S., & Wardat, Y. (2023). ChatGPT: Revolutionizing student achievement in the electronic magnetism unit for eleventh-grade students in Emirates schools. Contemporary Educational Technology, 15(4), ep448.
Alneyadi, S., Wardat, Y., Alshannag, Q., & Abu-Al-Aish, A. (2023). The effect of using smart e-learning app on the academic achievement of eighth-grade students. EURASIA Journal of Mathematics, Science and Technology Education, 19(4), em2248.
Aswin, A., & Herman, T. (2022). Self-efficacy in mathematics learning and efforts to improve it. Hipotenusa: Journal of Mathematical Society, 4(2), 185-198.
Balhoff, M. T., & Schmidt, K. J. (2022). Deeper thinking: One approach for teaching computer programming to undergraduates in numerical methods courses. In Proceedings of the 2010 GSW.
Caligaris, M. G., Rodríguez, G., & Laugero, L. (2015). Learning styles and visualization in numerical analysis. Procedia-Social and Behavioral Sciences, 174, 3696-3701.
Castillo, A. G. R., Silva, G. J. S., Arocutipa, J. P. F., Berrios, H. Q., Rodriguez, M. A. M., Reyes, G. Y., Lopez, H. R. P., Teves, R. M. V., Rivera, V. H. R., & Arias-Gonzáles, J. L. (2023). Effect of Chat GPT on the digitized learning process of university students. Journal of Namibian Studies, 33(S1), 1-15.
Dasuki, S. I., & Quaye, A. M. (2016). Undergraduate students’ failure in programming courses in institutions of higher education in developing countries: A Nigerian perspective. The Electronic Journal of Information Systems in Developing Countries, 76(1), 1-18.
Dinckal, C. (2018). Initial value problems spreadsheet solver using VBA for engineering education. Fundamental Journal of Mathematics and Applications, 1(1), 88-101.
Drijvers, P. (2000). Students encountering obstacles using a CAS. International Journal of Computers for Mathematical Learning, 5, 189-209.
Ekin, S. (2023). Prompt engineering for ChatGPT: A quick guide to techniques, tips, and best practices. TechRxiv.
Eyrikh, N. V., Markova, N. V., Zhunusakunova, A., Bazhenov, R. I., Matveeva, E. V., & Gorbunova, T. N. (2021). Using computer algebra system Maple for teaching the basics of the finite element method. In Proceedings of the 2021 International Conference on Quality Management, Transport and Information Security, Information Technologies (pp. 616-620).
Firdaus, D., Budiningsih, I., & Fauziah, S. (2021). The effect of using peer tutor methods and self-efficacy on math learning outcomes. Akademika: Jurnal Teknologi Pendidikan [Akademika: Journal of Educational Technology], 10(02), 371-382.
Gasull, A. (2017). Difference equations everywhere: Some motivating examples. In S. Elaydi, C. Pötzsche, & A. Sasu (Eds.), Difference equations, discrete dynamical systems and applications (pp. 129-167). Springer.
Gwynllyw, D. R., Henderson, K., van Lent, J., & Guillot, E. G. (2020). Using Python in the teaching of numerical analysis. MSOR Connections, 18(2), 25-32.
Handayani, A. D., Herman, T. L., & Fatimah, S. (2017). Developing teaching material software assisted for numerical methods. Journal of Physics: Conference Series, 895, 012068.
Hanum Siregar, F., Hasmayni, B., & Lubis, A. H. (2023). The analysis of Chat GPT usage impact on learning motivation among scout students. International Journal of Research and Review, 10(7), 632-638.
Heston, T. F. (2023). Prompt engineering for students of medicine and their teachers. Independently published.
Howe, D. K., & Barton, O. (2016). Developing an interactive computer program to enhance student learning of dynamical systems [Paper presentation]. The ASEE Annual Conference & Exposition.
Jarrah, A. M., Wardat, Y., & Fidalgo, P. (2023). Using ChatGPT in academic writing is (not) a form of plagiarism: What does the literature say? Online Journal of Communication and Media Technologies, 13(4), e202346.
Jatisunda, M. G., Suciawati, V., & Nahdi, D. S. (2020). Discovery learning with scaffolding to promote mathematical creative thinking ability and self-efficacy. Al-Jabar: Journal Pendidikan Matematika [Al-Jabar: Journal of Mathematics Education], 11(2), 351-370.
Ketcheson, D. I. (2014). Teaching numerical methods with IPython notebooks and inquiry-based learning. In Proceedings of the SciPy2014.
Krause, D. S. (2023). Proper generative AI prompting for financial analysis. SSRN.
Lappas, P. Z., & Kritikos, M. N. (2018). Teaching and learning numerical analysis and optimization: A didactic framework and applications of inquiry-based learning. Higher Education Studies, 8, 42-57.
Liang, Z., Yu, W., Rajpurohit, T., Clark, P., Zhang, X., & Kaylan, A. (2023). Let GPT be a math tutor: Teaching math word problem solvers with customized exercise generation. ArXiv.
Liao, W., Dong, N., & Fan, T. (2009). Application of Scilab in teaching of engineering numerical computations. In Proceedings of the 2009 IEEE International Workshop on Open-source Software for Scientific Computation (pp. 88-90).
Marotto, F. R. (2006). Introduction to mathematical modeling using discrete dynamical systems. Cengage Learning.
Martín-Caraballo, A. M., & Tenorio-Villalón, Á. F. (2015). Teaching numerical methods for non-linear equations with GeoGebra-based activities. International Electronic Journal of Mathematics Education, 10(2), 53-65.
Negara, H. R. P., Nurlaelah, E., Wahyudin, Herman, T., & Tamur, M. (2021). Mathematics self-efficacy and mathematics performance in online learning. Journal of Physics: Conference Series, 1882, 012050.
Nigmatulin, R., Vaguina, M. Y., & Kipnis, M. M. (2020). Educational potential of studying recurrence relations in the preparing of prospective mathematics teachers. Journal of Physics: Conference Series, 1691, 012047.
Owan, V. J., Abang, K. B., Idika, D. O., Etta, E. O., & Bassey, B. A. (2023). Exploring the potential of artificial intelligence tools in educational measurement and assessment. EURASIA Journal of Mathematics, Science and Technology Education, 19(8), em2307.
Ozmen, A., & Mumcu, H. Y. (2020). Investigation of empirical abstraction processes for slope concept according to students’ attitude, anxiety, motivation and self-efficacy perceptions towards mathematics. Inonu University Journal of the Faculty of Education, 21(2), 785-800.
Ruiz-Rojas, L. I., Acosta-Vargas, P., De-Moreta-Llovet, J., & Gonzalez-Rodriguez, M. (2023). Empowering education with generative artificial intelligence tools: Approach with an instructional design matrix. Sustainability, 15(15), 11524.
Sa, L., & Hsin, W. (2010). Traceable recursion with graphical illustration for novice programmers. InSight: A Journal of Scholarly Teaching, 5, 54-62.
Sahgal, A. (2023). Implementation of numerical methods for solving differential equations using Python. International Journal for Research Publication and Seminars, 14(4), 133-140.
Sárvári, C., & Klincsik, M. (2003). From iteration to one - dimensional discrete dynamical systems using CAS. Teaching Mathematics and Computer Science, 1, 271-296.
Seebut, S., Wongsason, P., Kim, D., Putjuso, T., & Boonpok, C. (2022). Python-based simulations of the probabilistic behavior of random events for secondary school students. EURASIA Journal of Mathematics, Science and Technology Education, 18(9), em2149.
Shang, X., Jiang, Z., Chiang, F., Zhang, Y., & Zhu, D. (2023). Effects of robotics STEM camps on rural elementary students’ self-efficacy and computational thinking. Educational Technology Research and Development, 71, 1135-1160.
Silva, P. H., Nardo, L. G., Martins, S. A., Nepomuceno, E. G., & Perc, M. (2018). Graphical interface as a teaching aid for nonlinear dynamical systems. European Journal of Physics, 39, 065105.
Simamora, R. E., Saragih, S., & Hasratuddin (2019). Improving students’ mathematical problem solving ability and self-efficacy through guided discovery learning in local culture context. International Electronic Journal of Mathematics Education, 14(1), 61-72.
Suharti, Sulasteri, S., Sari, N. N., Sriyanti, A., & Baharuddin. (2020). The development of teaching materials for subjects of numerical method assisted by MATLAB software in mathematics education department students. Journal of Physics: Conference Series, 1539, 012082.
Vasconcelos, M. A. R., & dos Santos, R. P. (2023). Enhancing STEM learning with ChatGPT and Bing Chat as objects to think with: A case study. EURASIA Journal of Mathematics, Science and Technology Education, 19(7), em2296.
Wardat, Y., Tashtoush, M. A., AlAli, R., & Jarrah, A. M. (2023). ChatGPT: A revolutionary tool for teaching and learning mathematics. EURASIA Journal of Mathematics, Science and Technology Education, 19(7), em2286.
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